SYSTEM FOR DETECTING VENTRICULAR COLLAPSE

Description

BACKGROUND OF THE INVENTION

1. FIELD OF THE INVENTION

[0001] The invention relates generally to implanted or implantable blood pump systems, and more specifically, to a system for detecting the onset and/or presence of ventricular collapse associated with such pumps.

2. DESCRIPTION OF RELATED ART

[0002] Generally, implantable blood pump systems are employed in either of two circumstances. First an implantable blood pump may completely replace a human heart that is not functioning properly, or second, an implantable blood pump may boost blood circulation in patients whose heart is still functioning although pumping at an inadequate rate.

[0003] For example, U.S. Patent No. 6,183,412, which is commonly assigned, discloses a ventricle assist device (VAD) commercially referred to as the "DeBakey VAD^®". The VAD is a miniaturized continuous axial-flow pump designed to provide additional blood flow to patients who suffer from heart disease. The device is attached between the apex of the left ventricle and the aorta. Proper blood flow through the device depends on an adequately filled ventricle and a positive differential pressure between the inlet and the outlet of the VAD pump.

[0004] Since this device produces flow continually and actively fills, it has the potential to create low pressure at the inflow in order to produce flow. "Excess Suction" occurs when the pressure in the inflow cannula decreases significantly - the pump begins to "suck" the ventricle closed, which would greatly reduce the pumping capability of the native heart and VAD. Decreasing the VAD's speed during an excess suction condition would allow the ventricle to refill, and normal blood flow to resume. Additionally, the detection of ventricular collapse and the ability to automatically adjust the pump's speed may aid in maintaining correct blood flow to the patient.

[0005] Excess suction may be caused by occlusion of the tip of the inflow cannula or by completely emptying the ventricle (ventricular collapse). In known pump systems, sustained excess suction typically triggers a diagnostic alarm on the pump controller. However, it would be desirable to detect the onset of suction prior to any physiologic effect. Additionally, it is typical of known methods that attempt to detect the onset or presence of ventricular collapse to use a binary "suction detect" flag when the onset of suction is believed to have been discovered. Information in addition to a simple binary indicator, however, is desirable as it would allow a physician or technician to make a more precise diagnosis.

[0006] US Patent No. 6,066,086 describes an automatic speed control system for continually adjusting the speed of an implanted cardiac assist blood pump to an optimum level for the varying physiological needs of the patient. It does this by periodically and iteratively incrementing the speed setpoint of the pump. When the system detects the imminence of a ventricular collapse at diastole, it decrements the speed setpoint by a predetermined safety margin. An alarm condition is also provided if the setpoint decrease results in an insufficient blood flow rate through the pump. The flow rate and imminence of ventricular collapse are computed in real time as functions of only the pump's motor current and speed setpoint.

[0007] EP-1046403-A1 describes a blood circulation assisting device using a continuous flow blood pump for blood feeding assistance to remove blood through a blood removing pipe and drive out blood at a predetermined flow rate through a blood feeding pipe. The blood circulation assisting device includes a current measuring unit for measuring current flowing through a motor driving the pump in order to use the current as data corresponding to a blood flow rate through the continuous flow blood pump and an amplitude detection unit for detecting, from an output of the current measuring unit, the amplitude of fluctuation of current flowing through the motor in order to use the amplitude as data corresponding to a flow rate amplitude due to flow rate fluctuation. The amplitude of this fluctuation is divided by an average current value and output as an amplitude index. By controlling the speed of the motor so that the amplitude index, which is the output of the amplitude detection unit, is within a predetermined value, a blood feeding assistance is kept in an optimum state matching a blood circulation state in an organism.

[0008] WO01/72352 describes a left ventricular assist device (LVAD) having a rotodynamic blood pump that is powered by a brushless DC motor, wherein a power supply supplies power to the motor. Three feedback channels, one for each of voltage, current and motor speed lead to a microcontroller or microprocessor. The three feedback waveforms are analyzed, and from these waveforms, motor input power, patient heart rate, current pump flow rate, and systemic pressure are determined. The microprocessor then calculates a desired flow rate proportional to the patient heart rate. The microprocessor communicates a new power output to a commutation circuit, which regulates power to the motor. The pump also includes safety checks that are prioritized over desired pump flow. These include prevention of ventricular suction, low pulsatility, minimum and maximum pump speed, minimum speed-relative pump flow, minimum absolute pump flow, minimum and maximum motor input power.

[0009] The present invention addresses shortcomings associated with the prior art.

SUMMARY OF THE INVENTION

[0010] In the present invention, an implantable pump system is provided as defined in claim 1.

BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Other objects and advantages of the invention will become apparent upon reading the following detailed description and upon reference to the drawings in which:

FIG. 1 schematically illustrates various components of an implantable pump system in accordance with embodiments of the present invention;

FIG. 2 is a cross-section view of an exemplary implantable pump in accordance with embodiments of the present invention;

FIG. 3 is a block diagram illustrating aspects of a controller module in accordance with embodiments of the present invention; and

FIGs. 4-9 are block diagrams conceptually illustrating methods of detecting ventricle collapse as described herein.

[0012] While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof have been shown by way of example in the drawings and are herein described in detail. It should be understood, however, that the description herein of specific embodiments is not intended to limit the invention to the particular forms disclosed, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the invention as defined by the appended claims.

DETAILED DESCRIPTION OF THE INVENTION

[0013] Illustrative embodiments of the invention are described below. In the interest of clarity, not all features of an actual implementation are described in this specification. It will of course be appreciated that in the development of any such actual embodiment, numerous implementation-specific decisions must be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which will vary from one implementation to another. Moreover, it will be appreciated that such a development effort might be complex and time-consuming, but would nevertheless be a routine undertaking for those of ordinary skill in the art having the benefit of this disclosure.

[0014] Turning to the figures, FIG. 1 illustrates a ventricle assist device (VAD) system 10 such as disclosed in U.S. Patent No. 6,183,412, which is commonly assigned and incorporated herein by reference in its entirety. The VAD system 10 includes components designed for implantation within a human body and components external to the body. Implantable components include a rotary pump 12 and a flow sensor 14. The external components include a portable controller module 16, a clinical data acquisition system (CDAS) 18, and a patient home support system (PHSS) 20. The implanted components are connected to the controller module 16 via a percutaneous cable 22.

[0015] The VAD System 10 may incorporate an implantable continuous-flow blood pump, such as the various embodiments of axial flow pumps disclosed in U.S. Patent No. 5,527,159 or in U.S. Patent No. 5,947,892, both of which are incorporated herein by reference in their entirety. An example of a blood pump suitable for use in an embodiment of the invention is illustrated in FIG. 2. The exemplary pump 12 includes a pump housing 32, a diffuser 34, a flow straightener 36, and a brushless DC motor 38, which includes a stator 40 and a rotor 42. The housing 32 includes a flow tube 44 having a blood flow path 46 therethrough, a blood inlet 48, and a blood outlet 50.

[0016] The stator 40 is attached to the pump housing 32, is preferably located outside the flow tube 44, and has a stator field winding 52 for producing a stator magnetic field. In one embodiment, the stator 40 includes three stator windings and may be three phase "Y" or "Delta" wound. The rotor 42 is located within the flow tube 44 for rotation in response to the stator magnetic field, and includes an inducer 58 and an impeller 60. Excitation current is applied to the stator windings 52 to generate a rotating magnetic field. A plurality of magnets 62 are coupled to the rotor 42. The magnets 62, and thus the rotor 42, follow the rotating magnetic field to produce rotary motion.

[0017] FIG. 3 conceptually illustrates aspects of the pump system 10. More specifically, portions of the controller module 16 and the pump 12 are shown. The controller module 16 includes a processor, such as a microcontroller 80, which in one embodiment of the invention is a model PIC 16C77 microcontroller manufactured by Microchip Technology. The microcontroller 80 includes a multiple channel analog to digital (A/D) converter, which receives indications of motor parameters from the motor controller 84. Thus, the controller module 16 may monitor parameters such as instantaneous motor current, motor voltage, and motor speed.

[0018] The invention shown in FIG. 3 includes an integral flow meter 124. At least one flow sensor 14 is implanted down stream of the pump 12. Alternately, a flow sensor 14 may be integrated with the pump 12. The flow meter 124 is coupled between the implanted flow sensor 14 and the microcontroller 80. The flow meter 124 receives data from the flow sensor 14 and outputs flow rate data to the microcontroller 80, allowing the system to monitor instantaneous flow rate.

[0019] Since the implanted flow sensor 14 is coupled to the flow meter 124 of the controller module 16, a true measure of system performance (flow rate) is available for analysis, in addition to pump parameters such as motor speed and current (power). Further, since the flow meter 124 is an integral component of the controller module 16, flow rate may be displayed on the controller module display and flow rate data may be saved in the controller module memory.

[0020] In exemplary embodiments of the invention, the motor controller 84 comprises a MicroLinear ML4425 Motor Controller from Fairchild Semiconductor. The operation of the brushless DC motor 38 of the present invention requires that current be applied in a proper sequence to the stator windings 52 to create the rotating field. Two stator windings 52 have current applied to them at any one time, and by sequencing the current on and off to the respective stator windings 52, the rotating magnetic field is produced. In an embodiment of the invention, the motor controller 84 senses back electromotive force (EMF) voltage from the motor windings 52 to determine the proper commutation phase sequence using phase lock loop (PLL) techniques. Whenever a conductor, such as a stator winding 52, is "cut" by moving magnetic lines of force, such as are generated by the magnets 62 of the brushless DC motor 38, a voltage is induced. The voltage will increase with rotor speed 42. It is possible to sense this voltage in one of the three stator windings 52 because only two of the motor's windings 52 are activated at any one time, to determine the rotor 42 position.

[0021] An alternative method of detecting the rotor 42 position relative to the stator 40 for providing the proper stator winding 52 excitation current sequence is to use a position sensor, such as a Hall effect sensor. Implementing aspects of the present invention using a motor with rotor position sensors, rather than a sensorless motor, would be a routine undertaking for one skilled in the art having the benefit of this disclosure. However, adding additional components, such as Hall effect sensors, requires additional space, which is limited in any implanted device application. Further, using a position detection device adds sources of system failures.

[0022] The motor controller 84 operates to maintain the pump 12 at an essentially constant speed regardless of the differential pressure across the pump or the flow through the pump. As noted above, the motor controller 84 uses a PLL to control the speed of the pump motor 38 (commutation control). An additional analog closed-loop control circuit controls the onboard pulse width modulator (PWM) to maintain a desired speed setting. Both control-loops work in unison to maintain proper speed control.

[0023] The motor controller 84 forms a PLL with a voltage-controlled oscillator (VCO), back-EMF sampling error amplifier, loop-filter, sequencer, and output driver. The motor controller 84 samples the instantaneous motor phase that is not energized to determine whether to increase or decrease the commutator (VCO) frequency. The VCO generates an output frequency (commutation rate) proportional to input voltage. A late commutation causes the error amplifier to charge the loop filter, increasing the VCO input while early commutation causes the error amplifier to discharge the loop filter, decreasing the VCO input. The PWM loop, operating at approximately 25 kHz in exemplary embodiments, effectively maintains the desired speed setting once the PLL has reached steady-state (the desired target speed). Constant speed control of the three-phase pump motor, under varying or pulsatile load conditions, is achieved by varying the amount of current delivered to the stator windings proportionally to the motor's load.

[0024] The commutation and PWM loops have, because of their associated filter networks, individual frequency and time domain responses associated with them. The frequency range over which the loop system will follow changes in the input frequency is called the lock-in range. The frequency range in which the loop acquires phase-lock is the capture range.

[0025] The dynamic characteristics of the phase-locked loop, and thus the way the pump motor responds to changes in load, are controlled primarily by the loop filter. The filter network included in the PLL serves two major functions. First, it removes any noise and high-frequency components from the error amplifer's output providing an average (dc) voltage to be fed to the VCO's input, and it is the primary element that determines the dynamic performance of the loop including capture (pull-in) range, lock-in range, bandwidth, and transient response.

[0026] Once the loop is phase-locked, the filter limits the speed of the loop to track changes in the input frequency (motor speed). In addition, the loop filter provides a "fly-wheel" effect, ensuring a rapid recapture of the signal if the system is thrown out of lock by a noise transient.

[0027] Variations in differential pressure across the pump 12 will impart instantaneous changes in the speed of the pump motor 38. The motor controller 84 will sense this change in speed through its back-EMF sampler and attempt to speed up or slow down the pump motor 38, such that the preset speed is maintained. This instantaneous load change and corresponding correction performed by the motor controller will result in a corresponding variation in the pump's current waveform, speed waveform, and flow waveform. An instantaneous increase in the pump's load will cause an instantaneous decrease in pump speed and thus an instantaneous increase in pump current and decrease in flow rate. Conversely, an instantaneous decrease in the pump's load will cause an instantaneous increase in pump speed and thus an instantaneous decrease in pump current and increase in flow rate.

[0028] Therefore, the pump's current (and therefore power), speed, and flow waveforms correlate well with changes in the pump's load. These waveforms may be used to calculate the patient's heart rate, instantaneous and mean blood flow rate, regurgitant flow, instantaneous and mean power consumption, the pump's efficiency, etc. These waveforms also indicate when the pump's speed is set too high and the ventricle begins to collapse. This condition exists when the flow and/or current waveforms are highly-asymmetric and/or their peaks appear to contain multiple ripples or are flattened (clipped). Additionally, waveforms with short negative rise-times (attack) followed by slower positive exponential fall-times (decay) indicate suction.

[0029] The aforementioned signals, current, speed, and flow, are time-continuous band-limited signals. The current signal is a composite signal containing the motor controller's PWM frequency, the patients heart rate (assuming the heart is beating), and other frequencies relating to certain physiologic responses within the patient's cardiovascular system (e.g. valve openings and closures, changes in systemic resistance, etc.). The pulse-width modulation frequency typically is approximately 25 kHz and the patient's heart rate is approximately 0.7 Hz to 4.0 Hz. A two-pole maximally flat low-pass Butterworth Filter (f_c=250 Hz) within the controller module 16 may be used to limit the bandwidth of this signal.

[0030] The power signal is the product of the pump motor current and pump motor voltage (a constant scalar) and is therefore a composite signal which, like the current, contains the motor controller's pulse-width modulation (PWM) frequency, the patient's heart rate (assuming there is a heart rate), and other frequencies relating to certain physiologic responses within the patient's cardiovascular system (e.g. valve openings and closures, changes in systemic resistance, etc.). The pulse-width modulation frequency is approximately 25 kHz and the patient's heart rate is approximately 0.7 Hz to 4.0 Hz.

[0031] The speed signal typically contains the heart rate of the patient (assuming the heart is beating) as the dominant frequency along with other frequencies related to certain physiologic responses within the patient's cardiovascular system (e.g. valve openings and closures, changes in systemic pressure, etc.). The angular momentum of the rotor impeller and viscosity of the blood dampen abrupt changes in speed and thus the bandwidth of this signal is typically under 30 Hz.

[0032] The flow signal typically contains the heart rate of the patient (assuming the heart is beating) as the dominant frequency along with other frequencies related to certain physiologic responses within the patient's cardiovascular system (e.g. valve openings and closures, changes in systemic pressure, etc.). A two-pole maximally flat low-pass Butterworth Filter (currently with fc=30 Hz) within the controller module 16 limits the bandwidth of this signal.

[0033] Described herein are various mechanisms to detect the onset and/or presence of ventricular collapse based on the processing and/or analysis of certain inherent pump system parameters (including flow, and optionally current, speed, etc.). These analysis techniques are performed in the time domain, and frequency domain. Time domain mechanisms include correlation techniques as well as linear and non-linear signal processing. Frequency domain mechanisms include various real-time spectral analysis methods using Fourier Transforms such as the Fast Fourier Transform ("FFT") and the Discrete Fourier Transform ("DFT"), as well as other linear and non-linear signal processing techniques.

[0034] In the time domain, a physiologically appropriate flow(t) waveform is assumed to be quasi-sinusoidal at a single frequency proportional to the patient's native heart rate (i.e. fundamental frequency). In the frequency domain, the corresponding physiologically appropriate flow(f) waveform will be a single narrow spectral peak at the same single frequency proportional to the patient's native heart rate. As the flow(t) waveform becomes more distorted (i.e. deviates from a perfect sinusoid), the flow(f) waveform will contain additional spectral peaks corresponding to flow contributions at varying frequencies.

[0035] The Fourier Series may be used to compute the fundamental and harmonic components from time domain signals that are continuous and periodic. Many in vivo waveforms that may denote suction, however, are not periodic, and further, the frequency components of such waveforms may not be harmonically related to the fundamental frequency. In accordance with aspects of the present invention, many frequency components, both harmonically related and not, about the fundamental are analyzed to precisely detect suction.

[0036] FIG. 4 illustrates ventricular collapse methods based on a spectral analysis as described herein. The embodiments shown in block diagram form in FIG. 4 operate on the principle that the onset of ventricular collapse is imminent when the flow and/or current waveforms are asymmetric and/or their peaks appear to contain multiple ripples or are flattened (clipped). Variations in the flow, speed, current, and power waveforms in the time-domain will result in corresponding variation in their frequency-domain representations.

[0037] In block 210, one or more time-continuous band-limited signals are received and converted to a digital signal. In certain embodiments, the flow signal provided via the flow sensor 14 and flow meter 124 is specifically analyzed for suction detection, though one or more of the current, power, speed, etc. signals available may be used. The spectral content of the sampled signals are computed in block 212. A Fourier Transform such as the Discrete Fourier Transform ("DFT"), and/or Fast Fourier Transform ("FFT") may be used to obtain the frequency-domain responses for the signals converted in block 210.

[0038] The FFT is more efficient computationally than is the DFT and is more easily realized in hardware and/or software. Continuous conversion of the time-continuous signals from the time-domain to the frequency-domain provides real time spectral content information about these signals. Referring to FIG. 4, the array generated in block 212 is processed by spectral analysis equations in block 214 to generate a suction probability index in block 216, which may be expressed as a percentage. The suction probability index provides an indication of the imminence of ventricle collapse in block 218. Known methods to detect the onset or presence of ventricular collapse use a binary "suction detect" indicator when onset is discovered. No "suction indices" are used. The use of "suction indices" leads to a more precise diagnosis and gives the physician access to more information than a simple binary answer.

[0039] Exemplary spectral analysis equations 214 used as described herein for processing the data to generate the suction probability index 216 include analyses based on harmonic distortion, total spectral distortion (harmonic distortion and noise), sub-fundamental distortion (distortion below the fundamental frequency), super-fundamental distortion (distortion above the fundamental frequency), the ratio of the super-fundamental distortion to the sub-fundamental distortion, super-physiologic distortion (distortion at frequencies above the assumed maximum physiologic fundamental frequency - typically 4Hz or 240 BPM), and the spectral dispersion or "width" of the resulting flow(f) waveform. These spectral analysis techniques are addressed in detail as follows.

[0040] The spectral distortion factor measures the ratio of all energy contributed by all frequencies about the fundamental frequency with respect to the fundamental frequency. A higher distortion ratio indicates a higher probability of suction.


wherein n indicates the spectral component's index/position in the resulting array; x is the last index/position in this array; dF represents the frequency resolution/interval of the resulting FFT operation in Hertz; and f₁ is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array. Since the spectral analysis of the flow rate signal pertains to the AC component, and not the offset, the range of interest does not include n=0 because the mean flow rate or DC component of the flow(f) waveform occurs at n=0. This is true for all of the frequency domain suction probability indices contained herein.

[0041] The harmonic distortion factor measures the ratio of energy contributed by all harmonics about the fundamental frequency with respect to the fundamental frequency.


wherein n indicates the n^th harmonic in the resulting array; x is the highest harmonic in this array; f₁ is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array; and f_n represents integer multiples of the fundamental f₁ from n=2 (second harmonic) to x (x^th harmonic).

[0042] The sub-fundamental distortion factor measures the additive frequency contributions below the fundamental frequency with respect to the fundamental frequency.

wherein n indicates the spectral component's index/position in the resulting array; dF represents the frequency resolution/interval of the resulting FFT operation in Hertz; f₁ is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array; and n(f1) is the index/position of the fundamental.

[0043] The super-fundamental distortion factor measures the additive frequency contributions above the fundamental frequency with respect to the fundamental frequency.


wherein n indicates the spectral component's index/position in the resulting array; x is the last index/position in this array; dF represents the frequency resolution/interval of the resulting FFT operation in Hertz; f₁ is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array; and n(f1) is the index/position of the fundamental.

[0044] The super/sub fundamental distortion factor measures the ratio of additive frequency contributions above the fundamental frequency to the additive frequency contributions below the fundamental frequency.


wherein n indicates the spectral component's index/position in the resulting array; dF represents the frequency resolution/interval of the resulting FFT operation in Hertz; x is the last index/position in this array; and n(f1) is the index/position of the fundamental.

[0045] The super physiologic distortion factor measures the additive frequency contributions above the maximum expected physiologic frequency (i.e. 4 Hz = 240 BPM) with respect to the fundamental frequency.


wherein f_h is a spectral peak at frequency = 4 Hz; n indicates the spectral component's index/position in the resulting array; x is the last index/position in this array; dF represents the frequency resolution/interval of the resulting FFT operation in Hertz; f₁ is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array.

[0046] In other embodiments, the spread of the waveform is measured. As noted above, it is assumed that a physiologically appropriate waveform in the time domain is quasi-sinusoidal at a single frequency proportional to the patient's native heart rate, and hence, the corresponding physiologically appropriate waveform in the frequency domain will be a singly narrow spectral peak at the same single frequency proportional to the patient's native heart rate. Deviations from this quasi-sinusoidal case may indicate suction as well as other defects.

[0047] For example, as the flow(t) waveform becomes more distorted, the flow(f) waveform will contain additional flow contributions at varying frequencies and will thus begin to "widen". The probability that suction is imminent or present increases proportionally to the width of flow(f). The measure of the width of ffow(f) about the fundamental frequency is the square-root of the mean-squared variation about the fundamental frequency. The spectral dispersion factor measures the "width" of the flow(f), current(f), speed(f), and/or power(f) signals:


wherein f₁ is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array; dF represents the frequency resolution/interval of the resulting FFT operation in Hertz; n indicates the spectral component's index/position in the resulting array; and N is the last index/position in this array. Since the analysis of spread flow is concerned with the wave shape, and not the offset, the range of interest does not include n=0 because the mean flow rate or DC component of the flow(f) waveform occurs at n=0.

[0048] Some alternatives to applying the spectral content of the measured signal to spectral analysis equations are shown in FIGs. 5 and 6, where the real time spectral content measured signal is compared to a predetermined spectral mask. In the embodiment shown in FIG. 5, the spectral content 220 generated by the FFT 212 is compared to a predetermined spectral mask 222 in a combiner block 224. In block 226, the presence of suction is determined based on the comparison. The signals whose spectral components fall within the mask indicate suction and, conversely, signals whose spectral components fall outside the mask indicate normal flow.

[0049] In the embodiment shown in FIG. 6, the time domain responses are converted to frequency domain through the application of a synchronous switched-capacitor filter 230. In this exemplary embodiment, the frequency response of the filter 230 is controlled by a clock source one hundred times the desired pass-band frequency. A phase-locked loop 232 generates this clocking signal to the filter 230 by receiving the output from a zero crossing detector 234 and multiplying the incoming fundamental frequency by an integer multiplier 236, the value of which is selected by a digital input element such as a microcontroller. Incrementing the integer multiplier will cause the synchronous filter to "track" the incoming signal and output the spectral amplitude of the fundamental frequency, first harmonic, second harmonic, etc. The sum of the individual spectral amplitudes results in a frequency-domain representation of the time-domain signals.

[0050] As in the embodiment illustrated in FIG. 5, a comparison may then be made between the real-time spectral content 220 of these signals and the predetermined spectral mask 222. Signals whose spectral components fall within the mask indicate suction and, conversely, signals whose spectral components fall outside the mask indicate normal flow.

[0051] Other embodiments described herein employ time domain analysis methods. FIG. 7 illustrates a method that cross-correlates the incoming time-sampled signal (for example, the flow or current signal) with predetermined time-domain waveforms 250 exemplifying the imminence of ventricular collapse. The waveforms 250 are selected in block 252 sequentially or based on the probability of occurrence in that particular patient derived experientially through clinical evaluation. A correlation coefficient is generated in block 254, where |R| = 1 signifies a perfect "match" and |R| = 0 indicates no correlation at all. The correlation coefficient is compared to predetermined thresholds in block 256 to derive a suction probability index. If the calculated correlation coefficient exceeds a predetermined value, ventricular collapse is imminent. Conversely, if the calculated correlation coefficient is below the predetermined value, suction is not present.

[0052] Alternatively, the incoming time-sampled signal may be cross-correlated with time-domain representations of sine waves at integer multiples of the incoming fundamental frequency. The sum of the individual spectral amplitudes results in a frequency-domain representation of the time-domain signals. A comparison is then made between the real-time spectral content of these signals and a predetermined spectral mask as in the embodiments shown in FIGs. 5 and 6. Signals whose spectral components fall within the mask indicate suction and, conversely, signals whose spectral components fall outside the mask indicate normal flow.

[0053] Still further analysis methods continuously time-sample signals representing system parameters including flow, and optionally speed, current, or power, and calculate the slope between a series of data points. By comparing the calculated slope to a predetermined value, ventricular collapse may be detected. This may also be applied to the first or second derivatives of the flow, current, speed, and/or power signals.

[0054] More specifically, as shown in block diagram form in FIG. 8, the derivative of the time- sampled signal, such as flow, with respect to time is calculated in block 260, which yields blood acceleration. Therefore, a large negative dflow(t)/dt indicates the presence of ventricular collapse. The calculated derivative is provided as one input to a comparitor 262. An adjustable suction detect threshold value 264 is provided as the second input to the comparitor 262 such that the derivative calculated in block 260 is compared to a predetermined value. Based on the output of the comparitor 262, the presence of collapse is determined in block 266.

[0055] Similarly, as shown in FIG. 9, the second derivative of the measured parameter (e.g. d²flow(t)/dt², d²current(t)/dt², d²power(t)/dt², or d²speed(t)/dt²) is calculated in block 261 and compared to a predetermined value to detect suction based on changes in the aforementioned signals.

[0056] In various embodiments described herein, the aforementioned methods for detecting the imminence of ventricular collapse are implemented in software, hardware, or both. Software implementations include using the microcontroller 80 used provided in the controller module 16. Alternatively, a stand-alone microcontroller or a digital signal processor ("DSP"), for example, may be used. Exemplary hardware implementations may include a field programmable gate array ("FPGA"), a complex programmable logic device ("CPLD"), application specific integrated circuits ("ASIC"), discrete analog and/or digital components, etc.

[0057] The particular embodiments disclosed above are illustrative only, as the invention may be modified and practiced in different but equivalent manners apparent to those skilled in the art having the benefit of the teachings herein. Furthermore, no limitations are intended to the details of construction or design herein shown, other than as described in the claims below. It is therefore evident that the particular embodiments disclosed above may be altered or modified and all such variations are considered within the scope of the invention. Accordingly, the protection sought herein is as set forth in the claims below.

Claims

1. An implantable continuous-flow blood pump system (10) capable of detecting a ventricular collapse, comprising:

a pump (12) including a motor (38) having a rotor (42) and a stator (40), the stator (40) including a plurality of stator windings (52);

a motor controller (16, 84) coupled to the motor (38); and

a processor (80) coupled to the motor controller (16, 84) for analyzing a time-based parameter of the pump, including a pump flow rate, and calculating a suction probability index that provides an indication of the imminence of ventricle collapse;

characterised in that the system further comprises an implantable flow sensing device (14) coupled to the processor (80), wherein the implantable flow sensing device (14) is arranged and operable to sample pump flow rate and to provide a flow signal representing pump flow rate to the processor (80) and wherein said processor (80) is arranged and operable to analyze the flow signal and, as a result, to output the suction probability index.

2. The implantable continuous-flow blood pump system of claim 1 , wherein the time-based system parameter of the blood pump further includes the pump current, or the pump speed.

3. The implantable continuous-flow blood pump system of claim 1, wherein the motor controller (16, 84) applies current to the stator windings (52) in a sequence to create a rotating field; and wherein the time-based parameter includes the stator winding current.

4. The implantable continuous-flow blood pump system of any one of claims 1 to 3, wherein the processor (80) is further configured to convert the sampled time-based parameter to a digital signal.

5. The implantable continuous-flow blood pump system of any one of claims 1 to 4, wherein the processor (80) is further configured to compute the spectral content of the sampled time-based signal.

6. The implantable continuous-flow blood pump system of claim 5, wherein the processor (80) is further configured to apply the computed spectral content to a spectral analysis equation to calculate the suction probability index.

7. The implantable continuous-flow blood pump system of claim 6, wherein the time-based system parameter is analyzed by computing the total distortion of the time-based system parameter waveform.

8. The implantable continuous-flow blood pump system of claim 7, wherein computing the spectral content includes applying a Fourier Transform, and wherein the suction probability index is calculated according to:


wherein n indicates the position of the spectral component in the array resulting from the Fourier Transform; x is the last position in the array; dF represents the frequency resolution/interval of the Fourier Transform in Hertz; and f₁ is the fundamental frequency, maximum (amplitude) spectral peak in the array.

9. The implantable continuous-flow blood pump system of any of claims 5 to 8, wherein the time-based system parameter is analyzed by computing the harmonic distortion of the time-based system parameter waveform.

10. The implantable continuous-flow blood pump system of claim 9, wherein computing the spectral content includes applying a Fourier Transform, and wherein the suction probability index is calculated according to:


wherein n indicates the n^th harmonic in the array resulting from the Fourier Transform; x is the last position in the array; f₁ is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array; and f_n represents integer multiples of the fundamental f₁ from n=2 (second harmonic) to x (x^th harmonic).

11. The implantable continuous-flow blood pump system of any of claims 5 to 10, wherein the time-based system parameter is analyzed by computing the distortion of the time-based system parameter waveform below the fundamental frequency.

12. The implantable continuous-flow blood pump system of claim 11, wherein computing the spectral content includes applying a Fourier Transform, and wherein the suction probability index is calculated according to:


wherein n indicates the position of the spectral component in the array resulting from the Fourier Transform; dF represents the frequency resolution of the Fourier Transform in Hertz; f₁ is the fundamental frequency, the maximum (amplitude) spectral peak in the Fourier Transform resultant array; and n(f1) is the position of the fundamental frequency in the array.

13. The implantable continuous-flow blood pump system of any of claims 5 to 12, wherein the time-based system parameter is analyzed by computing the distortion of the time-based system parameter waveform above the fundamental frequency.

14. The implantable continuous-flow blood pump system of claim 13, wherein computing the spectral content includes applying a Fourier Transform, and wherein the suction probability index is calculated according to:


wherein n indicates the position of the spectral component in the array resulting from the Fourier Transform; x is the last position in the array; dF represents the frequency resolution/interval of the Fourier Transform in Hertz; f₁ is the fundamental frequency, the maximum (amplitude) spectral peak in the array; and n(f1) is the position of the fundamental frequency in the array.

15. The implantable continuous-flow blood pump system of claim 13 or 14, wherein computing the spectral content further includes computing the ratio of additive frequency contributions above the fundamental frequency to the additive frequency contributions below the fundamental frequency, and wherein the suction probability index is calculated according to:


wherein n indicates the position of the spectral component in the array resulting from the Fourier Transform; x is the last position in the array; dF represents the frequency resolution/interval of the Fourier Transform in Hertz; f₁ is the fundamental frequency, the maximum (amplitude) spectral peak in the array; and n(f1) is the position of the fundamental frequency in the array.

16. The implantable continuous-flow blood pump system of any of claims 5 to 15, wherein the time-based system parameter is analyzed by computing the distortion of the time-based system parameter waveform above a predetermined physiologic frequency.

17. The implantable continuous-flow blood pump system of claim 16, wherein computing the spectral content includes applying a Fourier Transform, and wherein the suction probability index is calculated according to:


wherein f_h is a spectral peak at the predetermined physiologic frequency; n indicates the position of the spectral component in the array resulting from the Fourier Transform; x is the last position in the array; dF represents the frequency resolution/interval of the Fourier Transform in Hertz; f₁ is the fundamental frequency, the maximum (amplitude) spectral peak in the resultant array.

18. The implantable continuous-flow blood pump system of any of claims 5 to 17, wherein the time-based system parameter is analyzed by computing the spread of the time-based system parameter waveform.

19. The implantable continuous-flow blood pump system of claim 18, wherein computing the spectral content includes applying a Fourier Transform.

20. The implantable continuous-flow blood pump system of claim 19, wherein computing the spectral content includes applying the Fourier Transform, and wherein the suction probability index is calculated according to:


wherein f₁ is the maximum (amplitude) spectral peak in the array resulting from the Fourier Transform; dF represents the frequency resolution/interval of the Fourier Transform in Hertz; n indicates the position of the spectral component in the array; and N is the last position in the array.

21. The implantable continuous-flow blood pump system of any of claims 18 to 20, wherein computing the spectral content includes applying the sampled time-based signal to a synchronous switched-capacitor filter.

22. The implantable continuous-flow blood pump system of any one of claims 5 to 21, wherein the processor (80) is further configured to compare the computed spectral content to a predetermined spectral mask to calculate the suction probability index.

23. The implantable continuous-flow blood pump system of any preceding claim, wherein the time-based system parameter is analyzed by calculating the slope of the time-based system parameter.

24. The implantable continuous-flow blood pump system of claim 23, wherein calculating the suction probability index includes comparing the slope to a predetermined value.

25. The implantable continuous-flow blood pump system of claim 23 or 24, wherein calculating the slope includes calculating the first derivative or the second derivative of the time-based parameter.

Ansprüche

1. Implantierbares Durchfluss-Blutpumpensystem (10), das imstande ist, einen Ventrikelkollaps zu detektieren, umfassend:

eine Pumpe (12), enthaltend einen Motor (38) mit einem Rotor (42) und einem Stator (40), wobei der Stator (40) eine Mehrzahl von Statorwicklungen (52) enthält;

eine Motorsteuerung (16, 84), die mit dem Motor (38) verbunden ist; und

einen Prozessor (80), der mit der Motorsteuerung (16, 84) verbunden ist, zur Analyse eines zeitbasierten Parameters der Pumpe, einschließlich einer Pumpenströmungsrate, und Berechnen eines Saugwahrscheinlichkeitsindexes, der einen Hinweis auf einen bevorstehenden Ventrikelkollaps liefert;

dadurch gekennzeichnet, dass das System des Weiteren eine implantierbare Strömungserfassungsvorrichtung (14) umfasst, die mit dem Prozessor (80) verbunden ist, wobei die implantierbare Strömungserfassungsvorrichtung (14) so angeordnet und betreibbar ist, dass eine Pumpenströmungsrate abgetastet wird und ein Strömungssignal, das die Pumpenströmungsrate repräsentiert, dem Prozessor (80) bereitgestellt wird, und wobei der Prozessor (80) so ausgebildet und betreibbar ist, dass das Strömungssignal analysiert wird und als Ergebnis der Saugwahrscheinlichkeitsindex ausgegeben wird.

2. Implantierbares Durchfluss-Blutpumpensystem nach Anspruch 1, wobei der zeitbasierte Systemparameter der Blutpumpe des Weiteren den Pumpenstrom oder die Pumpendrehzahl enthält.

3. Implantierbares Durchfluss-Blutpumpensystem nach Anspruch 1, wobei die Motorsteuerung (16, 84) den Strom an die Statorwicklungen (52) in einer Sequenz anlegt, um ein Drehfeld zu erzeugen; und wobei der zeitbasierte Parameter den Statorwicklungsstrom enthält.

4. Implantierbares Durchfluss-Blutpumpensystem nach einem der Ansprüche 1 bis 3, wobei der Prozessor (80) des Weiteren so konfiguriert ist, dass der abgetastete zeitbasierte Parameter in ein digitales Signal umgewandelt wird.

5. Implantierbares Durchfluss-Blutpumpensystem nach einem der Ansprüche 1 bis 4, wobei der Prozessor (80) des Weiteren so konfiguriert ist, dass der Spektralinhalt des abgetasteten zeitbasierten Signals berechnet wird.

6. Implantierbares Durchfluss-Blutpumpensystem nach Anspruch 5, wobei der Prozessor (80) des Weiteren so konfiguriert ist, dass der berechnete Spektralinhalt bei einer Spektralanalysengleichung angewendet wird, um den Saugwahrscheinlichkeitsindex zu berechnen.

7. Implantierbares Durchfluss-Blutpumpensystem nach Anspruch 6, wobei der zeitbasierte Systemparameter durch Berechnen der Gesamtverzerrung der Wellenform des zeitbasierten Systemparameters analysiert wird.

8. Implantierbares Durchfluss-Blutpumpensystem nach Anspruch 7, wobei die Berechnung des Spektralinhalts das Anwenden einer Fourier-Transformation enthält, und wobei der Saugwahrscheinlichkeitsindex wie folgt berechnet wird:


wobei n die Position der Spektralkomponente in der Matrix angibt, die sich aus der Fourier-Transformation ergibt; x die letzte Position in der Matrix ist; dF die Frequenzauflösung/das Frequenzintervall der Fourier-Transformation in Hertz darstellt; und f₁ die Grundfrequenz, Maximal- (Amplituden-) Spektralspitze in der Matrix ist.

9. Implantierbares Durchfluss-Blutpumpensystem nach einem der Ansprüche 5 bis 8, wobei der zeitbasierte Systemparameter durch Berechnen der harmonischen Verzerrung der Wellenform des zeitbasierten Systemparameters analysiert wird.

10. Implantierbares Durchfluss-Blutpumpensystem nach Anspruch 9, wobei die Berechnung des Spektralinhalts das Anwenden einer Fourier-Transformation enthält, und wobei der Saugwahrscheinlichkeitsindex wie folgt berechnet wird:


wobei n die n. Harmonische in der Matrix angibt, die sich aus der Fourier-Transformation ergibt; x die letzte Position in der Matrix ist; f₁ die Grundfrequenz, die Maximal- (Amplituden-) Spektralspitze in der aus der FFT resultierenden Matrix ist; und f_n ganzzahlige Vielfache der Fundamentalen f₁ von n = 2 (zweite Harmonische) bis x (x. Harmonische) darstellt.

11. Implantierbares Durchfluss-Blutpumpensystem nach einem der Ansprüche 5 bis 10, wobei der zeitbasierte Systemparameter durch Berechnen der Verzerrung der Wellenform des zeitbasierten Systemparameters unter der Grundfrequenz analysiert wird.

12. Implantierbares Durchfluss-Blutpumpensystem nach Anspruch 11, wobei die Berechnung des Spektralinhalts das Anwenden einer Fourier-Transformation beinhaltet und wobei der Saugwahrscheinlichkeitsindex wie folgt berechnet wird:


wobei n die Position der Spektralkomponente in der Matrix angibt, die sich aus der Fourier-Transformation ergibt; dF die Frequenzauflösung der Fourier-Transformation in Hertz darstellt; f₁ die Grundfrequenz, die Maximal- (Amplituden-) Spektralspitze in der aus der Fourier-Transformation resultierenden Matrix ist; und n(f1) die Position der Grundfrequenz in der Matrix ist.

13. Implantierbares Durchfluss-Blutpumpensystem nach einem der Ansprüche 5 bis 12, wobei der zeitbasierte Systemparameter durch Berechnen der Verzerrung der Wellenform des zeitbasierten Systemparameters über der Grundfrequenz analysiert wird.

14. Implantierbares Durchfluss-Blutpumpensystem nach Anspruch 13, wobei die Berechnung des Spektralinhalts das Anwenden einer Fourier-Transformation beinhaltet und wobei der Saugwahrscheinlichkeitsindex wie folgt berechnet wird:


wobei n die Position der Spektralkomponente in der Matrix angibt, die sich aus der Fourier-Transformation ergibt; x die letzte Position in der Matrix ist; dF die Frequenzauflösung/das Frequenzintervall der Fourier-Transformation in Hertz darstellt; f₁ die Grundfrequenz, die Maximal- (Amplituden-) Spektralspitze in der Matrix ist; und n(f1) die Position der Grundfrequenz in der Matrix ist.

15. Implantierbares Durchfluss-Blutpumpensystem nach einem der Ansprüche 13 oder 14, wobei die Berechnung des Spektralinhalts des Weiteren das Berechnen des Verhältnisses additiver Frequenzbeiträge über der Grundfrequenz zu den additiven Frequenzbeiträgen unter der Grundfrequenz beinhaltet, und wobei der Saugwahrscheinlichkeitsindex wie folgt berechnet wird:


wobei n die Position der Spektralkomponente in der Matrix angibt, die sich aus der Fourier-Transformation ergibt; x die letzte Position in der Matrix ist; dF die Frequenzauflösung/das Frequenzintervall der Fourier-Transformation in Hertz darstellt; f₁ die Grundfrequenz, die Maximal- (Amplituden-) Spektralspitze in der Matrix ist; und n(f1) die Position der Grundfrequenz in der Matrix ist.

16. Implantierbares Durchfluss-Blutpumpensystem nach einem der Ansprüche 5 bis 15, wobei der zeitbasierte Systemparameter durch Berechnen der Verzerrung der Wellenform des zeitbasierten Systemparameters über einer vorbestimmten physiologischen Frequenz analysiert wird.

17. Implantierbares Durchfluss-Blutpumpensystem nach Anspruch 16, wobei die Berechnung des Spektralinhalts das Anwenden einer Fourier-Transformation beinhaltet und wobei der Saugwahrscheinlichkeitsindex wie folgt berechnet wird:


wobei f_h eine Spektralspitze bei der vorbestimmten physiologischen Frequenz ist; n die Position der Spektralkomponente in der Matrix angibt, die sich aus der Fourier-Transformation ergibt; x die letzte Position in der Matrix ist; dF die Frequenzauflösung/das Frequenzintervall der Fourier-Transformation in Hertz darstellt; f₁ die Grundfrequenz, die Maximal- (Amplituden-) Spektralspitze in der erhaltenen Matrix ist.

18. Implantierbares Durchfluss-Blutpumpensystem nach einem der Ansprüche 5 bis 17, wobei der zeitbasierte Systemparameter durch Berechnen der Ausbreitung der Wellenform des zeitbasierten Systemparameters analysiert wird.

19. Implantierbares Durchfluss-Blutpumpensystem nach Anspruch 18, wobei die Berechnung des Spektralinhalts das Anwenden einer Fourier-Transformation beinhaltet.

20. Implantierbares Durchfluss-Blutpumpensystem nach Anspruch 19, wobei die Berechnung des Spektralinhalts das Anwenden der Fourier-Transformation beinhaltet und wobei der Saugwahrscheinlichkeitsindex wie folgt berechnet wird:


wobei f₁ die Maximal- (Amplituden-) Spektralspitze in der Matrix ist, die sich aus der Fourier-Transformation ergibt; dF die Frequenzauflösung/das Frequenzintervall der Fourier-Transformation in Hertz darstellt; n die Position der Spektralkomponente in der Matrix angibt; und N die letzte Position in der Matrix ist.

21. Implantierbares Durchfluss-Blutpumpensystem nach einem der Ansprüche 18 bis 20, wobei die Berechnung des Spektralinhalts das Anlegen des abgetasteten zeitbasierten Signals an einen synchronen Filter mit geschaltetem Kondensator enthält.

22. Implantierbares Durchfluss-Blutpumpensystem nach einem der Ansprüche 5 bis 21, wobei der Prozessor (80) des Weiteren so konfiguriert ist, dass der berechnete Spektralinhalt mit einer vorbestimmten Spektralmaske verglichen wird, um den Saugwahrscheinlichkeitsindex zu berechnen.

23. Implantierbares Durchfluss-Blutpumpensystem nach einem der vorangehenden Ansprüche, wobei der zeitbasierte Systemparameter durch Berechnung der Steigung des zeitbasierten Systemparameters analysiert wird.

24. Implantierbares Durchfluss-Blutpumpensystem nach Anspruch 23, wobei das Berechnen des Saugwahrscheinlichkeitsindexes das Vergleichen der Steigung mit einem vorbestimmten Wert enthält.

25. Implantierbares Durchfluss-Blutpumpensystem nach Anspruch 23 oder 24, wobei das Berechnen der Steigung das Berechnen der ersten Ableitung oder der zweiten Ableitung des zeitbasierten Parameters auf Zeitbasis.

Revendications

1. Système de pompe sanguine à écoulement continu implantable (10) capable de détecter un collapsus ventriculaire, comprenant :

une pompe (12) comportant un moteur (38) présentant un rotor (42) et un stator (40), le stator (40) comportant une pluralité d'enroulements de stator (52) ;

un dispositif de commande de moteur (16, 84) couplé au moteur (38) ; et

un processeur (80) couplé au dispositif de commande de moteur (16, 84) et destiné à analyser un paramètre basé sur le temps de la pompe, comportant un débit de la pompe, et à calculer un indice de probabilité de succion indiquant l'imminence du collapsus ventriculaire ;

caractérisé en ce que le système comprend en outre un dispositif de détection d'écoulement implantable (14) couplé au processeur (80), dans lequel le dispositif de détection d'écoulement implantable (14) est conçu et capable de fonctionner pour échantillonner le débit de la pompe et fournir un signal d'écoulement représentant le débit de la pompe au processeur (80) et dans lequel ledit processeur (80) est conçu et capable de fonctionner pour analyser le signal d'écoulement et, en conséquence, afficher l'indice de probabilité de succion.

2. Système de pompe sanguine à écoulement continu implantable selon la revendication 1, dans lequel le paramètre de système basé sur le temps de la pompe sanguine comporte en outre le courant de la pompe, ou la vitesse de la pompe.

3. Système de pompe sanguine à écoulement continu implantable selon la revendication 1, dans lequel le dispositif de commande de moteur (16, 84) applique un courant sur les enroulements de stator (52) dans une séquence pour créer un champ rotatif ; et dans lequel le paramètre basé sur le temps comporte le courant de l'enroulement de stator.

4. Système de pompe sanguine à écoulement continu implantable selon l'une quelconque des revendications 1 à 3, dans lequel le processeur (80) est en outre configuré pour convertir le paramètre échantillonné basé sur le temps en signal numérique.

5. Système de pompe sanguine à écoulement continu implantable selon l'une quelconque des revendications 1 à 4, dans lequel le processus (80) est en outre configuré pour calculer la répartition spectrale du signal échantillonné basé sur le temps.

6. Système de pompe sanguine à écoulement continu implantable selon la revendication 5, dans lequel le processeur (80) est en outre configuré pour appliquer la répartition spectrale calculée sur une équation d'analyse spectrale pour calculer l'indice de probabilité de succion.

7. Système de pompe sanguine à écoulement continu implantable selon la revendication 6, dans lequel le paramètre de système basé sur le temps est analysé par calcul de la distorsion totale de la forme d'onde du paramètre de système basé sur le temps.

8. Système de pompe sanguine à écoulement continu implantable selon la revendication 7, dans lequel le calcul de la répartition spectrale comporte l'application d'une transformée de Fourier, et dans lequel l'indice de probabilité de succion est calculé selon :


dans lequel n indique la position du composant spectral dans le groupement résultant de la transformée de Fourier ; x est la dernière position dans le groupement ; dF représente la résolution de fréquence/ l'intervalle de la transformée de Fourier en Hertz ; et f₁ est la fréquence fondamentale, la crête spectrale maximale (amplitude) dans le groupement.

9. Système de pompe sanguine à écoulement continu implantable selon l'une quelconque des revendications 5 à 8, dans lequel le paramètre de système basé sur le temps est analysé par calcul de la distorsion harmonique de la forme d'onde du paramètre de système basé sur le temps.

10. Système de pompe sanguine à écoulement continu implantable selon la revendication 9, dans lequel le calcul de la répartition spectrale comporte l'application d'une transformée de Fourier, et dans lequel l'indice de probabilité de succion est calculé selon :


dans lequel n indique le n^ième harmonique dans le groupement résultant de la transformée de Fourier ; x est la dernière position dans le groupement ; f₁ est la fréquence fondamentale, la crête spectrale maximale (amplitude) dans le groupement résultant dans la TFR ; et f_n représente des multiples entiers de la fondamentale f₁ de n=2 (seconde harmonique) à x (x^ième harmonique).

11. Système de pompe sanguine à écoulement continu implantable selon l'une quelconque des revendications 5 à 10, dans lequel le paramètre de système basé sur le temps est analysé par calcul de la distorsion de la forme d'onde du paramètre de système basé sur le temps au-dessous de la fréquence fondamentale.

12. Système de pompe sanguine à écoulement continu implantable selon la revendication 11, dans lequel le calcul de la répartition spectrale comporte l'application d'une transformée de Fourier, et dans lequel l'indice de probabilité de succion est calculé selon :


dans lequel n indique la position du composant spectral dans le groupement résultant de la transformée de Fourier ; dF représente la résolution de fréquence de la transformée de Fourier en Hertz ; f₁ est la fréquence fondamentale, la crête spectrale maximale (amplitude) dans le groupement résultant de la transformée de Fourier ; et n(f1) est la position de la fréquence fondamentale dans le groupement.

13. Système de pompe sanguine à écoulement continu implantable selon l'une quelconque des revendications 5 à 12, dans lequel le paramètre de système basé sur le temps est analysé par calcul de la distorsion de la forme d'onde du paramètre de système basé sur le temps au-dessus de la fréquence fondamentale.

14. Système de pompe sanguine à écoulement continu implantable selon la revendication 13, dans lequel le calcul de la répartition spectrale comporte l'application d'une transformée de Fourier, et dans lequel l'indice de probabilité de succion est calculé selon :


dans lequel n indique la position du composant spectral dans le groupement résultant de la transformée de Fourier ; x est la dernière position dans le groupement ; dF représente la résolution de fréquence/l'intervalle de la transformée de Fourier en Hertz ; f₁ est la fréquence fondamentale, la crête spectrale maximale (amplitude) dans le groupement ; et n(f1) est la position de la fréquence fondamentale dans le groupement.

15. Système de pompe sanguine à écoulement continu implantable selon la revendication 13 ou 14, dans lequel le calcul de la répartition spectrale comporte le calcul du rapport des contributions additives de fréquence au-dessus de la fréquence fondamentale aux contributions additives de fréquence au-dessous de la fréquence fondamentale, et dans lequel l'indice de probabilité de succion est calculé selon :


dans lequel n indique la position du composant spectral dans le groupement résultant de la transformée de Fourier ; x est la dernière position dans le groupement ; dF représente la résolution de fréquence/l'intervalle de la transformée de Fourier en Hertz ; f₁ est la fréquence fondamentale, la crête spectrale maximale (amplitude) dans le groupement ; et n(f1) est la position de la fréquence fondamentale dans le groupement.

16. Système de pompe sanguine à écoulement continu implantable selon l'une quelconque des revendications 5 à 15, dans lequel le paramètre de système basé sur le temps est analysé par calcul de la distorsion de la forme d'onde du paramètre de système basé sur le temps au-dessus d'une fréquence physiologique prédéterminée.

17. Système de pompe sanguine à écoulement continu implantable selon la revendication 16, dans lequel le calcul de la répartition spectrale comporte l'application d'une transformée de Fourier, et dans lequel l'indice de probabilité de succion est calculé selon :


dans lequel f_h est une crête spectrale à la fréquence physiologique prédéterminée ; n indique la position du composant spectral dans le groupement résultant de la transformée de Fourier ; x est la dernière position dans le groupement ; dF représente la résolution de fréquence/l'intervalle de la transformée de Fourier en Hertz ; f₁ est la fréquence fondamentale, la crête spectrale maximale (amplitude) dans le groupement résultant.

18. Système de pompe sanguine à écoulement continu implantable selon l'une quelconque des revendications 5 à 17, dans lequel le paramètre de système basé sur le temps est analysé par calcul de l'étalement de la forme d'onde du paramètre de système basé sur le temps.

19. Système de pompe sanguine à écoulement continu implantable selon la revendication 18, dans lequel le calcul de la répartition spectrale comporte l'application d'une transformée de Fourier.

20. Système de pompe sanguine à écoulement continu implantable selon la revendication 19, dans lequel la répartition spectrale comporte l'application de la transformée de Fourier, et dans lequel l'indice de probabilité de succion est calculé selon :


dans lequel f₁ est la crête spectrale maximale (amplitude) dans le groupement résultant de la transformée de Fourier ; dF représente la résolution de fréquence/l'intervalle de la transformée de Fourier en Hertz ; n indique la position du composant spectral dans le groupement ; et N est la dernière position dans le groupement.

21. Système de pompe sanguine à écoulement continu implantable selon l'une quelconque des revendications 18 à 20, dans lequel le calcul de la répartition spectrale comporte l'application du signal échantillonné basé sur le temps sur un filtre synchrone à capacités commutées.

22. Système de pompe sanguine à écoulement continu implantable selon l'une quelconque des revendications 5 à 21, dans lequel le processeur (80) est en outre configuré pour comparer la répartition spectrale calculée à un masque spectral prédéterminé pour calculer l'indice de probabilité de succion.

23. Système de pompe sanguine à écoulement continu implantable selon l'une quelconque des revendication précédentes, dans lequel le paramètre de système basé sur le temps est analysé par calcul de la pente du paramètre de système basé sur le temps.

24. Système de pompe sanguine à écoulement continu implantable selon la revendication 23, dans lequel le calcul de l'indice de probabilité de succion comporte la comparaison de la pente à une valeur prédéterminée.

25. Système de pompe sanguine à écoulement continu implantable selon la revendication 23 ou 24, dans lequel le calcul de la pente comporte le calcul de la première dérivée ou de la seconde dérivée du paramètre basé sur le temps.

Drawing